AWS Fargate is now available in the Africa (Cape Town) Region.  

Amazon Kinesis Data Analytics now provides enhanced monitoring for Apache Flink applications through new metrics sent to Amazon CloudWatch. Amazon Kinesis Data Analytics emits 19 application metrics by default such as CPU and memory utilization. You can also easily create custom metrics in your application code using Apache Flink’s built-in metrics system.  

Amazon Connect contact center agents that have completed a call or chat and log out of the latest version of the Contact Control Panel (CCP) will now set to Offline agent status. When your agents log in to the CCP, they can set the agent status to Available to start answering calls or chats. Previously, agents had to change current status (e.g. Available, Custom statuses such as “Lunch”, “Break”) to Offline before logging out to not receive contacts. 

Android users can now use Amazon API Gateway, AWS CloudTrail, AWS Identity and Access Management, AWS Lambda, and Amazon Simple Queue Service features on the Console mobile app. In addition, we have expanded Amazon CloudWatch capabilities to include logs. 

The AWS Deep Learning Containers are available today with the latest framework versions of 1.15.2 with python 3.7 support . The release includes updates to the Amazon SageMaker Experiments package. Amazon SageMaker Experiments is a feature in Amazon SageMaker that lets you organize, track, compare, and evaluate machine learning (ML) experiments and model versions. The TensorFlow 1.15.2 python3.7 training containers now also include SageMaker Debugger , which allow data scientists to save and inspect the model tensors during training jobs.

The AWS Deep Learning Containers for Elastic Inference are available today with the framework versions PyTorch 1.3.1, TensorFlow 1.15.0, and TensorFlow 2.0.0. The PyTorch 1.3.1 upgrade includes the newly added SageMaker Inference and SageMaker PyTorch Inference. The TensorFlow 1.15.0 and TensorFlow 2.0.0 upgrades include the latest versions of TensorFlow Model Server for use with Elastic Inference. You can launch the new versions of the Deep Learning Containers on Amazon SageMaker, on Amazon EC2, and on Amazon Elastic Container Service (Amazon ECS). For a complete list of packages and versions supported by these Deep Learning Containers, see the release notes .

Today, Amazon WorkMail announced that you can now control email flow of your organization using AWS Lambda functions when using Email Flow Rules. With this, you can build powerful email flow control system with completely customizable conditions. For example, you can easily create Lambda to block any specific type of inbound or outbound email, or you can add or remove recipients to all or some inbound or outbound email. 

Amazon Kendra is now generally available to all AWS customers, with exciting new feature additions. Amazon Kendra provides customers with a highly accurate and easy to use enterprise search service powered by machine learning. Kendra offers a more intuitive way to search, using natural language, and returns more accurate answers; so your end users can discover information stored within the vast amount of content spread across your organization. Users can ask questions like “How long is maternity leave?” and get a specific answer such as “14 weeks”, or “How do I configure my VPN?” and get a specific passage extracted from a document describing the process. With Kendra, you can provide pinpoint search accuracy from content within your manuals, research reports, FAQs, HR documentation, customer service guides, and more. 

The AWS Deep Learning Containers are available today with the latest framework versions of PyTorch 1.5.0, with newly added SageMaker Inference, SageMaker PyTorch Inference, and the latest version of SageMaker PyTorch Training. You can launch the new versions of the Deep Learning Containers on Amazon SageMaker, Amazon Elastic Kubernetes Service (Amazon EKS), self-managed Kubernetes on Amazon EC2, and Amazon Elastic Container Service (Amazon ECS). For a complete list of frameworks and versions supported by the AWS Deep Learning Containers, see the release notes for PyTorch 1.5.0.

AWS Direct Connect makes it easy to establish a dedicated network connection from your premises to AWS. Using AWS Direct Connect, you can establish private connectivity between AWS and your data center, office, or colocation environment, which in many cases can reduce your network costs, increase bandwidth throughput, and provide a more consistent network experience than Internet-based connections.